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4. row minima method example ( Enter your problem )
Algorithm and examples
  1. Algorithm & Example-1
  2. Example-2
  3. Unbalanced supply and demand example
Other related methods
  1. north-west corner method
  2. least cost method
  3. vogel's approximation method
  4. Row minima method
  5. Column minima method
  6. Russell's approximation method
  7. Heuristic method-1
  8. Heuristic method-2
  9. modi method (optimal solution)
  10. stepping stone method (optimal solution)

3. vogel's approximation method
(Previous method)
2. Example-2
(Next example)

1. Algorithm & Example-1





Algorithm
Row minima method Steps (Rule)
Step-1: In this method, we allocate as much as possible in the lowest cost cell of the first row, i.e. allocate `min(s_i, d_j)`.
Step-2: a. Subtract this `min` value from supply `s_i` and demand `d_j`.

b. If the supply `s_i` is 0, then cross (strike) that row and If the demand `d_j` is 0 then cross (strike) that column.

c. If min unit cost cell is not unique, then select the cell where maximum allocation can be possible
Step-3: Repeat this process for all uncrossed (unstriked) rows and columns until all supply and demand values are 0.

Example-1
1. Find Solution using Row minima method
D1D2D3D4Supply
S1193050107
S2703040609
S3408702018
Demand58714


Solution:
TOTAL number of supply constraints : 3
TOTAL number of demand constraints : 4
Problem Table is
`D_1``D_2``D_3``D_4`Supply
`S_1`193050107
`S_2`703040609
`S_3`408702018
Demand58714


In `1^(st)` row, The smallest transportation cost is 10 in cell `S_1 D_4`.

The allocation to this cell is min(7,14) = 7.
This exhausts the capacity of `S_1` and leaves 14 - 7 = 7 units with `D_4`

Table-1
`D_1``D_2``D_3``D_4`Supply
`S_1`19305010(7)0
`S_2`703040609
`S_3`408702018
Demand5877


In `2^(nd)` row, The smallest transportation cost is 30 in cell `S_2 D_2`.

The allocation to this cell is min(9,8) = 8.
This satisfies the entire demand of `D_2` and leaves 9 - 8 = 1 units with `S_2`

Table-2
`D_1``D_2``D_3``D_4`Supply
`S_1`19305010(7)0
`S_2`7030(8)40601
`S_3`408702018
Demand5077


In `2^(nd)` row, The smallest transportation cost is 40 in cell `S_2 D_3`.

The allocation to this cell is min(1,7) = 1.
This exhausts the capacity of `S_2` and leaves 7 - 1 = 6 units with `D_3`

Table-3
`D_1``D_2``D_3``D_4`Supply
`S_1`19305010(7)0
`S_2`7030(8)40(1)600
`S_3`408702018
Demand5067


In `3^(rd)` row, The smallest transportation cost is 20 in cell `S_3 D_4`.

The allocation to this cell is min(18,7) = 7.
This satisfies the entire demand of `D_4` and leaves 18 - 7 = 11 units with `S_3`

Table-4
`D_1``D_2``D_3``D_4`Supply
`S_1`19305010(7)0
`S_2`7030(8)40(1)600
`S_3`4087020(7)11
Demand5060


In `3^(rd)` row, The smallest transportation cost is 40 in cell `S_3 D_1`.

The allocation to this cell is min(11,5) = 5.
This satisfies the entire demand of `D_1` and leaves 11 - 5 = 6 units with `S_3`

Table-5
`D_1``D_2``D_3``D_4`Supply
`S_1`19305010(7)0
`S_2`7030(8)40(1)600
`S_3`40(5)87020(7)6
Demand0060


In `3^(rd)` row, The smallest transportation cost is 70 in cell `S_3 D_3`.

The allocation to this cell is min(6,6) = 6.
Table-6
`D_1``D_2``D_3``D_4`Supply
`S_1`19305010(7)0
`S_2`7030(8)40(1)600
`S_3`40(5)870(6)20(7)0
Demand0000


Initial feasible solution is
`D_1``D_2``D_3``D_4`Supply
`S_1`19 30 50 10 (7)7
`S_2`70 30 (8)40 (1)60 9
`S_3`40 (5)8 70 (6)20 (7)18
Demand58714


The minimum total transportation cost `= 10 xx 7 + 30 xx 8 + 40 xx 1 + 40 xx 5 + 70 xx 6 + 20 xx 7 = 1110`

Here, the number of allocated cells = 6 is equal to m + n - 1 = 3 + 4 - 1 = 6
`:.` This solution is non-degenerate


This material is intended as a summary. Use your textbook for detail explanation.
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3. vogel's approximation method
(Previous method)
2. Example-2
(Next example)





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